Penerapan Machine Learning untuk Menganalisis dan Mencegah Kejahatan Cyber di Tengah Peringatan Seragan Digital Menggunakan Algoritma Random Forest

GUDARE, Yohanes Brian (2025) Penerapan Machine Learning untuk Menganalisis dan Mencegah Kejahatan Cyber di Tengah Peringatan Seragan Digital Menggunakan Algoritma Random Forest. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

The rapid advancement of information technology has had a significant impact across various sectors, but it has also opened up vulnerabilities to the growing threat of cyberattacks. These attacks often target network systems and digital data belonging to individuals, institutions, and corporations, posing considerable risks and losses. Therefore, a more intelligent and adaptive approach is needed to detect and analyze suspicious network activities. This study aims to implement a Machine Learning method using the randomf forest algorithm to identify abnormal traffic patterns as a form of cybercrime. The research process includes collecting cyberattack data, cleaning the data, training the model, and evaluating classification results. The developed system is integrated into a web-based interface to facilitate real-time monitoring and provide critical information related to suspicious activities within the network. The results of this study demonstrate that applying the Random Forest algorithm contributes significantly to the early detection of cyberattacks and serves as an effective preventive solution to enhance digital network security.

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